This invention relates to methods of business and economic modeling that rely on mathematical and computer models to predict possible future economic and business activity. These methods often rely upon mathematical algorithms and/or combinations of mathematical algorithms to ascertain an expected future result.
Other methods of economic and business modeling focus on simply detecting the future state of an economic or business system, perhaps to determine when it is wise to invest in stocks, bonds, currency or commodities. At times these models have relied upon rather “straightforward” methods of analysis to arrive at their predictions. In these models input values are entered, run through the series of calculations the model requires and a determination is made regarding the future business and economic state. However, these models are not reflective of a real business and economic system as these systems are dynamic, nonlinear, and “Chaotic”.
Dynamically nonlinear systems dominate the inner workings of nature. They determine the interaction of fluids on our planet, thus weather patterns, air and water currents, and influence the natural formation of solid structures. Further, dynamically nonlinear patterns are found in biological systems, from how a tree may grow, to how nerves and blood vessels extend throughout the body of an animal. However, the influence of dynamic nonlinearity is felt outside the realm of nature as well.
It is recognized that societies tend to produce chaotic, nonlinear patterns as well, including macro-economic systems. By recognizing the patterns that exist in these macro-economic systems, it possible to make more accurate predictions regarding what the possible future state of a market may be. Thus, some economic prediction models may adopt nonlinearity as a component in their economic and/or market forecasts.
However, even these economic models do not provide business and economic leaders with all the information that may be valuable in their decision making processes. They fail to consider what types of changes caused by new innovations may lead to a fundamental shift in the existing marketplace. Without a model designed to recognize such game changing innovations, the currently existing models fail to address a vitally important business and economic decision making need. The current invention provides such a dynamically nonlinear model to detect such innovations.
Thus, what is needed is an improved business modeling method that detects innovations that have disruptive business effects within an economic/market system allowing for a user to make business decisions with a more complete set of information.